HW3-drafting-viz
1 Question 1:
Which option do you plan to pursue? It’s okay if this has changed since HW #1.
I’m still planning on pursuing the infographic.
2 Question 2:
Restate your question(s). Has this changed at all since HW #1? If yes, how so?
My questions have shifted slightly since Homework 1 -
How have major air pollutants trended over the last 10–20 years in Los Angeles, CA?
Which pollutants are the biggest contributors to poor AQI?
- It’s PM 2.5
Which areas of Los Angeles are most affected by PM2.5?
What are the sources of PM2.5?
3 Question 3:
Explain which variables from your data set(s) you will use to answer your question(s), and how.
To see how air pollution as trended over time, I’ve used AQI Summary data from the EPA. I was able to calculate the median AQI per year from 2000-2024, giving me two variables, AQI (number) and year (number). Using the same AQI data, I was able to see the main pollutants contributing to the AQI by grouping by year and pollutant to see the top pollutants per year. I was then able to average those counts to get the top pollutant count for 2000-2024, giving me two variables, main pollutant (chr) and average count (number).
To see which areas are most affected by PM 2.5 in Los Angeles, I used CalEnviroscreen data. After tidying the spatial data to show only the incorporated regions of Los Angeles County, I was able to plot PM 2.5 percentile across the county. The variables I’ve filtered and selected for in the Enviroscreen data include PM 2.5 percentile (num), tract (num), zip (num), geometry (sfc). I kept zip code for quick area reference.
To see the sources of PM 2.5, I tidied and wrangled two datasets, Point Sources and Nonpoint Sources, from the EPA’s National Emissions Inventory (NEI) for the most recent year available (2020). After joining the datasets, I was left with three variables: pollution source (chr), source type (chr), and total emissions (num).
4 Question 4:
- Find at least two data visualizations that you could (potentially) borrow / adapt pieces from. Link to them or download and embed them into your
.qmdfile, and explain which elements you might borrow (e.g. the graphic form, legend design, layout, etc.).
Loving this infographic by Neel Dhanesha. I’ve been struggling to figure out to put my final viz together. I like how this infographic is very data driven but has many strategic annotaions and well as short paragraphs to explain each graph and move the story forward. I may try a similar spacing, and longer captions.
Giorgia Lupi was one of my favorite finds while exploring other visualizations - she often mixes photography, illustration, and digital elements into her visualization, which i find so beautiful…almost like mixed media art. I dont think I will be making any graphs with photos like this one, but I did find a photo of Los Angeles to base my color scheme off of, and I’d like to incorporate some hand drawn elements into my infographic.
5 Question 5:
- Hand-draw your anticipated visualizations, then take a photo of your drawing(s) and embed it in your rendered
.qmdfile – note that these are not exploratory visualizations, but rather your plan for your final visualizations that you will eventually polish and submit with HW #4. You should have a sketch of your infographic (which should include at least three component visualizations) if you are pursuing option 1.